Bayesian approximations and extensions: Optimal decisions for small brains and possibly big ones too

We compared the performance of Bayesian learning strategies and approximations to such strategies, which are far less computationally demanding, in a setting requiring individuals to make binary decisions based on experience. Extending Bayesian updating schemes, we compared the different strategies while allowing for various implementations of memory and knowledge about the environment. The dynamics of the observable variables was modeled …